POS0096 SJÖGREN’S DISEASE AND SYSTEMIC LUPUS ERYTHEMATOSUS DDX6-CXCR5 RISK INTERVALS REVEAL COMMON SNPS WITH FUNCTIONAL SIGNIFICANCE IN IMMUNE AND SALIVARY GLAND CELLS
Authors: M. M. Wiley, B. Khatri, K. L. Tessneer, M. L. Joachims, A. M. Stolarczyk, A. Nagel, A. Rasmussen, S. J. Bowman, L. Radfar, R. Omdal, M. Wahren-Herlenius, B. M. Warner, T. Witte, R. Jonsson, M. Rischmueller, P. M. Gaffney, J. A. James, L. Ronnblom, R. H. Scofield, X. Mariette, W. F. Ng, K. Sivils, G. Nordmark, B. Tsao, C. Lessard
Journal: Annals of the Rheumatic Diseases (2022)

Background Sjögren’s Disease (SjD) and Systemic Lupus Erythematosus (SLE) are autoimmune diseases with several shared characteristics and similar genome-wide significant associations with the DDX6-CXCR5 locus. DDX6 suppresses interferon-stimulated gene expression and CXCR5 regulates T cell functions implicated in autoimmunity. Objectives To identify and characterize functional SNPs in the DDX6-CXCR5 interval. Methods ImmunoChip data from European populations (3785 SLE cases; 1916 SjD cases; 6893 controls) were imputed and SNP-trait associations tested. Bayesian statistics defined a credible SNP set that was refined using bioinformatic analyses (RegulomeDB, Haploreg, ENCODE, promoter capture Hi-C, eQTLs, etc.). Electrophoretic mobility shift assays (EMSAs) and luciferase expression assays were used to test allele-specific SNP function in EBV-transformed B (EBV B) cells, Daudi B cells, Jurkat T cells, THP1 monocytes, and A253 salivary gland cell lines. Chromatin conformation capture with quantitative PCR (3C-qPCR) was used to assess long-range chromatin interactions. Results Fine mapping of the SjD and SLE associations found similar SNP associations. Bioinformatic analyses identified 5 common SNPs with strong evidence of functionality in immune cell types: rs57494551 in an intron of DDX6, and rs4938572, rs4936443, rs7117261, and rs4938573 in the promoter/enhancer region of DDX6 and CXCR5 . EMSAs and luciferase experiments showed cell type-specific differences in protein binding and promoter or enhancer activity, respectively, at each SNP. Risk allele of rs57494551 increased enhancer activity in B cells and A253 cells (p&lt;0.001), but decreased promoter activity in T cells and A253 cells (p&lt;0.01). SNP rs4938572 is an eQTL of DDX6 in T cells, and the risk allele significantly increased protein binding, promoter and enhancer activity in T cells (p&lt;0.01). Risk allele of rs4938572 also increased promoter activity in A253 cells (p&lt;0.001), but had no effect on promoter or enhancer activity in B cells. SNP rs4936443 showed no promoter or enhancer activity in immune cells, but the risk allele showed significant promoter and enhancer (p&lt;0.001) activity in A253 cells. SNP rs7117261 showed decreased enhancer activity in EBV B cells, T cells, and A253 cells (p&lt;0.05) and increased promoter activity in A253 cells (p&lt;0.001). SNP rs4938573 showed decreased promoter activity in EBV B cells, T cell and A253 cells (p&lt;0.05), decreased promoter activity in EBV B cells (p&lt;0.05), and increased enhancer activity in A253 cells (p&lt;0.0001). Overall, A253 cells exhibited more allele-specific effects on promoter and enhancer activity across the five SNPs compared to tested immune cells. In addition to DDX6 and CXCR5 , rs57494551 and/or rs4938572 are reported eQTLs for several other genes of interest in the local chromatin regulatory network: IL10RA in T cells, TRAPPC4 in salivary gland and activated macrophages, and long non-coding (lnc)RNA AP002954.1 in T cells and whole blood. 3C-qPCR in EBV B and A253 cells showed that the two regulatory regions carrying rs4938572 or rs57494551 interacted with a region upstream of DDX6 that includes AP002954.1 . Hi-C data showed looping between AP002954.1 and the regulatory region carrying rs4938572 and rs57494551 in T cells. Conclusion SjD and SLE share similar genomic architecture across the DDX6-CXCR5 risk interval with several common SNPs showing immune and salivary gland cell type-specific allelic effects on protein binding and/or enhancer/promoter activity. Extensive bioinformatic analyses suggest that the SNPs likely work within the local chromatin regulatory network to regulate cell type-specific expression of several genes on the interval. Ongoing studies will use 3C-qPCR to assess allele-specific chromatin interactions between the SNPs and these genes in different cells types, and CRISPR to determine how the risk alleles alters expression. Disclosure of Interests Mandi M Wiley: None declared, Bhuwan Khatri: None declared, Kandice L Tessneer: None declared, Michelle L Joachims: None declared, Anna M Stolarczyk: None declared, Anna Nagel: None declared, Astrid Rasmussen: None declared, Simon J. Bowman Consultant of: Abbvie, Galapagos, and Novartis in 2020-2021, Lida Radfar: None declared, Roald Omdal: None declared, Marie Wahren-Herlenius: None declared, Blake M Warner: None declared, Torsten Witte: None declared, Roland Jonsson: None declared, Maureen Rischmueller: None declared, Patrick M Gaffney: None declared, Judith A. James: None declared, Lars Ronnblom: None declared, R Hal Scofield: None declared, Xavier Mariette: None declared, Wan Fai Ng: None declared, Kathy Sivils Employee of: current employee of Janssen., Gunnel Nordmark: None declared, Betty Tsao: None declared, Christopher Lessard: None declared